Dynamics, Adaptation, and Control for Mental Models Analysed from a Self-modeling Network Viewpoint

Laila van Ments, Raj Bhalwankar, Jan Treur*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

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Abstract

This chapter contributes an analysis of how in mental and social processes, humans often apply specific mental models and learn and adapt them in a controlled manner. It is discussed how controlled adaptation relates to the Plasticity Versus Stability Conundrum in neuroscience. From the analysis an informal three-level cognitive architecture for controlled adaptation was obtained. It is discussed here from a self-modeling network viewpoint how this cognitive architecture can be modeled as a self-modeling network. Making use of the specific network characteristics offered by the self-modeling network structure format, a large number of options for different types of adaptation of mental models and different types of control over adaptation of mental models were obtained. Many of these options were illustrated by a several realistic examples that were formalized by self-modeling networks. Other options that were distinguished from the analysis here, are offered as interesting options for future research.

Original languageEnglish
Title of host publicationMental Models and their Dynamics, Adaptation and Control
Subtitle of host publicationA Self-Modeling Network Modeling Approach
EditorsJan Treur, Laila Van Ments
PublisherSpringer Nature Switzerland AG
Chapter21
Pages585-605
Number of pages21
ISBN (Electronic)9783030858216
ISBN (Print)9783030858209
DOIs
Publication statusPublished - 2022

Publication series

NameStudies in Systems, Decision and Control
Volume394
ISSN (Print)2198-4182
ISSN (Electronic)2198-4190

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Adaptation
  • Control
  • Dynamics
  • Mental models

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